Feasibility of Spectroscopic Characterization of Algal Lipids: Chemometric Correlation of NIR and FTIR Spectra with Exogenous Lipids in Algal Biomass

A large number of algal biofuels projects rely on a lipid screening technique for selecting a particular algal strain with which to work. We have developed a multivariate calibration model for predicting the levels of spiked neutral and polar lipids in microalgae, based on infrared (both near-infrared (NIR) and Fourier transform infrared (FTIR)) spectroscopy. The advantage of an infrared spectroscopic technique over traditional chemical methods is the direct, fast, and non-destructive nature of the screening method. This calibration model provides a fast and high-throughput method for determining lipid content, providing an alternative to laborious traditional wet chemical methods. We present data of a study based on nine levels of exogenous lipid spikes (between 1% and 3% (w/w)) of trilaurin as a triglyceride and phosphatidylcholine as a phospholipid model compound in lyophilized algal biomass. We used a chemometric approach to corrrelate the main spectral changes upon increasing phospholipid and triglyceride content in algal biomass collected from single species. A multivariate partial least squares (PLS) calibration model was built and improved upon with the addition of multiple species to the dataset. Our results show that NIR and FTIR spectra of biomass from four species can be used to accurately predict the levels of exogenously added lipids. It appears that the cross-species verification of the predictions is more accurate with the NIR models (R ²?=?0.969 and 0.951 and RMECV?=?0.182 and 0.227% for trilaurin and phosphatidylcholine spike respectively), compared with FTIR (R ²?=?0.907 and 0.464 and RMECV?=?0.302 and 0.767% for trilaurin and phosphatidylcholine spike, respectively). A fast high-throughput spectroscopic lipid fingerprinting method can be applied in a multitude of screening efforts that are ongoing in the microalgal research community.     

Mid‐infrared spectroscopy‐based analysis of mammalian cell culture Parameters

Within the framework of process analytical technology, infrared spectroscopy (IR) has been used for characterization of biopharmaceutical production processes. Although noninvasive attenuated total reflection (ATR) spectroscopy can be regarded as gold standard within IR‐based process analytics, simpler and more cost‐effective mid‐infrared (MIR) instruments might improve acceptability of this technique for high‐level monitoring of small scale experiments as well as for academia where financial restraints impede the use of costly equipment. A simple and straightforward at‐line mid‐IR instrument was used to monitor cell viability parameters, activity of lactate dehydrogenase (LDH), amount of secreted antibody, and concentration of glutamate and lactate in a Chinese hamster ovary cell culture process, applying multivariate prediction models, including only 25–28 calibration samples per model. Glutamate amount could be predicted with high accuracy (R² 0.91 for independent test‐set) while antibody concentration achieved good prediction for concentrations >0.4 mg L^?1. Prediction of LDH activity was accurate except for the low activity regime. The model for lactate monitoring was only moderately good and requires improvements. Relative cell viability between 20 and 95% could be predicted with low error (8.82%) in comparison to reference methods. An initial model for determining the number of nonviable cells displayed only acceptable accuracy and requires further improvement. In contrast, monitoring of viable cell number showed better accuracy than previously published ATR‐based results. These results prove the principal suitability of less sophisticated MIR instruments to monitor multiple parameters in biopharmaceutical production with relatively low investments and rather fast calibration procedures. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:578–584, 2015     

In situ near infrared spectroscopy for analyte‐specific monitoring of glucose and ammonium in streptomyces coelicolor fermentations

There are many challenges associated with in situ collection of near infrared (NIR) spectra in a fermentation broth, particularly for highly aerated and agitated fermentations with filamentous organisms. In this study, antibiotic fermentation by the filamentous bacterium Streptomyces coelicolor was used as a model process. Partial least squares (PLS) regression models were calibrated for glucose and ammonium based on NIR spectra collected in situ. To ensure that the models were calibrated based on analyte‐specific information, semisynthetic samples were used for model calibration in addition to data from standard batches. Thereby, part of the inherent correlation between the analytes could be eliminated. The set of semisynthetic samples were generated from fermentation broth from five separate fermentations to which different amounts of glucose, ammonium, and biomass were added. This method has previously been used off line but never before in situ. The use of semisynthetic samples along with validation on an independent batch provided a critical and realistic evaluation of analyte‐specific models based on in situ NIR spectroscopy. The prediction of glucose was highly satisfactory resulting in a RMSEP of 1.1 g/L. The prediction of ammonium based on NIR spectra collected in situ was not satisfactory. A comparison with models calibrated based on NIR spectra collected off line suggested that this is caused by signal attenuation in the optical fibers in the region above 2,000 nm; a region which contains important absorption bands for ammonium. For improved predictions of ammonium in situ, it is suggested to focus efforts on enhancing the signal in that particular region. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2010     

Assessment of ATR‐NIR and ATR‐MIR spectroscopy as an analytical tool for the quantification of the total polyphenols in Dendrobium huoshanense

In this study, the potentiality of applying attenuated total reflectance near‐infrared (ATR‐NIR) and attenuated total reflectance mid‐infrared (ATR‐MIR) techniques combined with a partial least squares (PLS) regression technology to quantify the total polyphenols (TPs) in Dendrobium huoshanense (DHS) was investigated and compared. The real TP contents in the DHS samples were analysed using methods of reference. The capability of the two IR spectroscopic techniques to quantify the TPs in DHS was assessed by the root‐mean‐square error of calibration (RMSEC) and determination coefficients (R²). The results showed that both NIR and MIR might be used as a fast and simple tool to replace traditional chemical assays for the determination of the TP contents in DHS, and the best NIR model showed slightly better prediction performance [root‐mean‐square error of prediction (RMSEP): 0.307, R²: 0.9122, ratio performance deviation (RPD): 4.43] than the best MIR model (RMSEP: 0.440, R²: 0.9069, RPD: 3.09). Results from this study indicated that both the NIR and MIR models could be used to quantify the TP in DHS, and ATR‐NIR appeared to be the more predominant and more robust technique for the quantification of the TP in DHS.     

Near‐infrared spectroscopic evaluation of lyophilized viral vaccine formulations

This article examines the applicability of near‐infrared spectroscopy (NIRS) to evaluate the virus state in a freeze‐dried live, attenuated vaccine formulation. Therefore, this formulation was freeze‐dried using different virus volumes and after applying different pre‐freeze‐drying virus treatments (resulting in different virus states): (i) as used in the commercial formulation; (ii) without antigen (placebo); (iii) concentrated via a centrifugal filter device; and (iv) stressed by 96 h exposure to room temperature. Each freeze‐dried product was measured directly after freeze‐drying with NIR spectroscopy and the spectra were analyzed using principal component analysis (PCA). Herewith, two NIR spectral regions were evaluated: (i) the 7300–4000 cm^?1 region containing the amide A/II band which might reflect information on the coated proteins of freeze‐dried live, attenuated viruses; and (ii) the C–H vibration overtone regions (10,000–7500 and 6340–5500 cm^?1) which might supply information on the lipid layer surrounding the freeze‐dried live, attenuated viruses. The different pre‐freeze‐drying treated live, attenuated virus formulations (different virus states and virus volumes) resulted in different clusters in the scores plots resulting from the PCA of the collected NIR spectra. Secondly, partial least squares discriminant analysis models (PLS‐DA) were developed and evaluated, allowing classification of the freeze‐dried formulations according to virus pretreatment. The results of this study suggest the applicability of NIR spectroscopy for evaluating live, attenuated vaccine formulations with respect to their virus pretreatment and virus volume. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29:1573–1586, 2013     

Quantitation of drug content in a low dosage formulation by transmission near infrared spectroscopy

A transmission near infrared (NIR) spectroscopic method has been developed for the nondestructive determination of drug content in tablets with less than 1% weight of active ingredient per weight of formulation (m/m) drug content. Tablets were manufactured with drug concentrations of ∼0.5%, 0.7%, and 1.0% (m/m) and ranging in drug content from 0.71 to 2.51 mg per tablet. Transmission NIR spectra were obtained for 110 tablets that constituted the training set for the calibration model developed with partial least squares regression. The reference method for the calibration model was a validated UV spectrophotometric method. Several data preprocessing methods were used to reduce the effect of scattering on the NIR spectra and base the calibration model on spectral changes related to the drug concentration changes. The final calibration model included the spectral range from 11 216 to 8662 cm⁻¹ the standard normal variate (SNV), and first derivative spectral pretreatments. This model was used to predict an independent set of 48 tablets with a root mean standard error of prediction (RMSEP) of 0.14 mg, and a bias of only −0.05 mg per tablet. The study showed that transmission NIR spectroscopy is a viable alternative for nondestructive testing of low drug content tablets, available for the analysis of large numbers of tablets during process development and as a tool to detect drug agglomeration and evaluate process improvement efforts. Published: March 24, 2006     

Hemodialysis monitoring using mid‐ and near‐infrared spectroscopy with partial least squares regression

Blood constituents such as urea, glucose, lactate, phosphate and creatinine are of high relevance in monitoring the process of detoxification in ambulant dialysis treatment. In the present work, 2 different vibrational spectroscopic techniques are used to determine those molecules quantitatively in artificial dialysate solutions. The goal of the study is to compare the performance of near‐infrared (NIR) and mid‐infrared (MIR) spectroscopy in hyphenation with partial least squares regression (PLSR) directly by using the same sample set. The results show that MIR spectroscopy is better suited to analyze the analytes of interest. Multilevel multifactor design is used to cover the relevant concentration variations during dialysis. MIR spectroscopy coupled to a multi reflection attenuated total reflection (ATR) cell enables reliable prediction of all target analytes. In contrast, the NIR spectroscopic method does not give access to all 5 components but only to urea and glucose. For both methods, coefficients of determination greater or equal to 0.86 can be achieved in the test‐set validation process for urea and glucose. Lactate, phosphate and creatinine perform well in the MIR with R² ≥ 0.95 using test‐set validation.      

Acoustic-resonance spectrometry as a process analytical technology for the quantification of active pharmaceutical ingredient in semi-solids

The purpose of this study was to demonstrate acoustic resonance spectrometry (ARS) as an alternative process analytical technology to near infrared (NIR) spectroscopy for the quantification of active pharmaceutical ingradient (API) in semi-solids such as creams, gels, ointments, and lotions. The ARS used for this research was an inexpensive instrument constructed from readily available parts. Acoustic-resonance spectra were collected with a frequency spectrum from 0 to 22.05 KHz. NIR data were collected from 1100 to 2500 nm. Using 1-point net analyte signal (NAS) calibration, NIR for the API (colloidal oatmeal [CO]) gave anr ² prediction accuracy of 0.971, and a standard error of performance (SEP) of 0.517%CO. ARS for the API resulted in anr ² of 0.983 and SEP of 0.317%CO. NAS calibration is compared with principal component regression. This research demonstrates that ARS can sometimes outperform NIR spectrometry and can be an effective analytical method for the quantification of API in semi-solids. ARS requires no sample preparation, provides larger penetration depths into lotions than optical techniques, and measures API concentrations faster and more accurately. These results suggest that ARS is a useful process analytical technology (PAT). Published: July 14, 2006     

Cross‐sex genetic covariances limit the evolvability of wing‐shape within and among species of Drosophila

The independent evolution of males and females is potentially constrained by both sexes inheriting the same alleles from their parents. This genetic constraint can limit the evolvability of complex traits; however, there are few studies of multivariate evolution that incorporate cross‐sex genetic covariances in their predictions. Drosophila wing‐shape has emerged as a model high‐dimensional phenotype; wing‐shape is highly evolvable in contemporary populations, and yet perplexingly stable across phylogenetic timescales. Here, we show that cross‐sex covariances in Drosophila melanogaster, given by the B ‐matrix, may considerably bias wing‐shape evolution. Using random skewers, we show that B would constrain the response to antagonistic selection by 90%, on average, but would double the response to concordant selection. Both cross‐sex within‐trait and cross‐sex cross‐trait covariances determined the predicted response to antagonistic selection, but only cross‐sex within‐trait covariances facilitated the predicted response to concordant selection. Similar patterns were observed in the direction of extant sexual dimorphism in D. melanogaster, and in directions of most and least dimorphic variation across the Drosophila phylogeny. Our results highlight the importance of considering between‐sex genetic covariances when making predictions about evolution on both macro‐ and microevolutionary timescales, and may provide one more explanatory piece in the puzzle of stasis.     

Application of NIR Spectroscopy Coupled with PLS Regression for Quantification of Total Polyphenol Contents from the Fruit and Aerial Parts of Citrullus colocynthis

Introduction

Citrullus colocynthis (L.) Schrad is extensively used to treat diabetes, obesity, fever, cancer, amenorrhea, jaundice, leukemia, rheumatism, and respiratory diseases. Chemical studies have indicated the presence of several cucurbitacins, flavones, and other polyphenols in this plant. These phytochemical constituents are responsible for the interesting antioxidant and other biological activities of C. colocynthis.

Objective

In the present study, for the first time, near infrared (NIR) spectroscopy coupled with partial least square (PLS) regression analysis was used to quantify the polyphenolic phytochemicals of C. colocynthis.

Methodology

The fruit and aerial parts of the C. colocynthis were extracted individually in methanol followed by fractionation in n‐hexane, chloroform, ethyl acetate, n‐butanol, and water. Near infrared (NIR) spectra were obtained in absorption mode in the wavelength range 700–2500 nm. The PLS regression model was then built from the obtained spectral data to quantify the total polyphenol contents in the selected plant samples.

Results

The PLS regression model obtained had a R² value of 99% with a 0.98 correlationship value and a good prediction with a root mean square error of prediction (RMSEP) value of 1.89% and correlation of 0.98. These results were further confirmed through UV–vis spectroscopy and it is found that the ethyl acetate fraction has the maximum value for polyphenol contents (101.7 mg/100 g; NIR, 100.4 mg/100 g; UV–vis).

Conclusions

The polyphenolic phytochemicals of the fruit and aerial parts of C. colocynthis have been quantified successfully by using multivariate analysis in a non‐destructive, economical, precise, and highly sensitive method, which uses very simple sample preparation. Copyright © 2017 John Wiley & Sons, Ltd.     

Investigation of the effect of clinically relevant interferents on glucose monitoring using near-infrared spectroscopy

Near infrared spectroscopy (NIR) is a promising technique for continuous blood glucose monitoring for diabetic patients. Four interferents, at physiological concentrations, were introduced to study how the glucose predictions varied with a standard multivariate calibration model. Lactate and ethanol were found to interfere strongly with the glucose predictions unless they were included in the calibration models. Lactate was mistaken for glucose and gave erroneously high glucose predictions, with a dose response of 0.46 mM/mM. The presence of ethanol resulted in too low glucose predictions, with a dose response of −0.43 mM/mM. Acetaminophen, a known interferent in the glucose monitoring devices used for diabetes management today, was not found to be an interferent in NIR spectroscopy, nor was caffeine. Thus, interferents that may appear in high concentrations, such as ethanol and lactate, must be included in the calibration or model building of future NIR-based glucose measurement devices for diabetes monitoring.     

Pefabloc – A sulfonyl fluoride serine protease inhibitor blocks induction of Diptericin in Drosophila l(2)mbn cells

Abstract Insects protect themselves against microbial infection by an efficient innate immune system that is activated by recognition of invariant microbial surface molecules. In the fruit fly Drosophila melanogaster the presence of bacteria is associated with expression of antimicrobial peptides in host immune‐competent tissues. Host receptors detect infection and relay the signal to mount the appropriate immune response. In Drosophila hemocyte‐like l(2)mbn cells pre‐infection treatment with Pefabloc, a commonly used serine protease inhibitor, induced two major effects: it blocked expression of the antibacterial peptide Diptericin in response to live Gram‐negative bacteria and bacterial surface molecules (crude lipopolysaccharide contaminated by peptidoglycans) and it induced morphological changes.     

Identification of a genetic network for an ecologically relevant behavioural phenotype in Drosophila melanogaster

Pupation site choice of Drosophila third‐instar larvae is critical for the survival of individuals, as pupae are exposed to various biotic and abiotic dangers while immobilized during the 3–4 days of metamorphosis. This singular behavioural choice is sensitive to both environmental and genetic factors. Here, we developed a high‐throughput phenotyping approach to assay the variation in pupation height in Drosophila melanogaster, while controlling for possibly confounding factors. We find substantial variation of mean pupation height among sampled natural stocks and we show that the Drosophila Genetic Reference Panel (DGRP) reflects this variation. Using the DGRP stocks for genome‐wide association (GWA) mapping, 16 loci involved in determining pupation height could be resolved. The candidate genes in these loci are enriched for high expression in the larval central nervous system. A genetic network could be constructed from the candidate loci, which places scribble (scrib) at the centre, plus other genes known to be involved in nervous system development, such as Epidermal growth factor receptor (Egfr) and p53. Using gene disruption lines, we could functionally validate several of the initially identified loci, as well as additional loci predicted from network analysis. Our study shows that the combination of high‐throughput phenotyping with a genetic analysis of variation captured from the wild can be used to approach the genetic dissection of an environmentally relevant behavioural phenotype.     

Prediction of Tablet Film-coating Thickness Using a Rotating Plate Coating System and NIR Spectroscopy

The purpose of this research was to create a calibration model based on near-infrared (NIR) spectroscopy data obtained during a small-scale coating process to predict in-line the coating layer thickness of tablets coated in a side-vented drum coater. The developed setup for the small-scale coating process consisted of a rotating plate with 20 tablets molds that pass a spraying unit, a heating unit, and an in-line NIR spectroscopy probe during one rotation. High-density polyethylene (HDPE) was compressed to flat-faced tablets, and these were coated with a sustained release coating suspension containing Kollicoat IR and Kollicoat SR 30D. The film thickness of these tablets was determined for each tablet individually with a digital micrometer. A calibration model of predicted film thickness versus real-film thickness using PLS regression was developed. This model was tested against in-line NIR data obtained from a coating drum process, in which biconvex HDPE tablets were film-coated with the same film-coating suspension. The model predicted a final coating thickness of 240 μm, while the measured average thickness (n = 100 tablets) was 210 μm. Taking into account the use of a different setup and differently shaped tablets, it was possible to predict the coating thickness with accuracy comparable to the one of the digital micrometer. Thus, the small-scale rotating plate system was found to be an efficient means of preparing calibration model for a tablet-coating drum process.     

Near infrared spectroscopy and aquaphotomics: Novel approach for rapid in vivo diagnosis of virus infected soybean

Near infrared spectroscopy with aquaphotomics as a novel approach was assessed for the diagnosis of soybean plants (Glycine max) infected with soybean mosaic virus (SMV) at latent symptomless stage of the disease. Near infrared (NIR) leaf spectra (in the range of 730-1025 nm) acquired from soybean plants with and without the inoculation of SMV were used. Leaf samples from all plants were assayed with enzyme-linked immunosorbent assay (ELISA) to confirm the infection. Previously reported NIR band for water at 970 nm and two new bands at 910 nm and 936 nm in the water specific region of NIR were found to be markedly sensitive to the SMV infection 2 weeks prior to the appearance of visual symptoms on infected leaves. The spectral calibration model soft independent modeling of class analogy (SIMCA), predicted the disease with 91.6% sensitivity and 95.8% specificity when the second order derivative of the individual plant averaged spectra were used. The study shows the potential of NIR spectroscopy with its novel approach to elucidate latent biochemical and biophysical information of an infection as it allowed successful discrimination of SMV infected plant from healthy at the early symptomless stage of the disease.     

Out of the testis,into the ovary: biased outcomes of gene duplication and deletion in Drosophila

Gene turnover is a key source of adaptive variation. Yet most evolutionary studies have focused on gene duplication, dismissing gene deletion as a mechanism that simply eradicates redundancy. Here, I use genome‐scale sequence and multi‐tissue expression data from Drosophila melanogaster and Drosophila pseudoobscura to simultaneously assess the evolutionary outcomes of gene duplication and deletion in Drosophila. I find that gene duplication is more frequent than gene deletion in both species, indicating that it may play a more important role in Drosophila evolution. However, examination of several genic properties reveals that genes likely possess distinct functions after duplication that diverge further before deletion, suggesting that loss of redundancy cannot explain a majority of gene deletion events in Drosophila. Moreover, in addition to providing support for the well‐known “out of the testis” origin of young duplicate genes, analyses of gene expression profiles uncover a preferential bias against deletion of old ovary‐expressed genes. Therefore, I propose a novel “into the ovary” hypothesis for gene deletion in Drosophila, in which gene deletion may promote adaptation by salvaging genes that contribute to the evolution of female reproductive phenotypes. Under this combined “out of the testis, into the ovary” evolutionary model, gene duplication and deletion work in concert to generate and maintain a balanced repertoire of genes that promote sex‐specific adaptation in Drosophila.     

Cis- and trans-acting genetic factors contribute to heterogeneity in the rate of crossing over between the Drosophila simulans clade species

In the genus Drosophila, variation in recombination rates has been found within and between species. Genetic variation for both cis‐ and trans‐acting factors has been shown to affect recombination rates within species, but little is known about the genetic factors that affect differences between species. Here, we estimate rates of crossing over for seven segments that tile across the euchromatic length of the X chromosome in the genetic backgrounds of three closely related Drosophila species. We first generated a set of Drosophila mauritiana lines each having two semidominant visible markers on the X chromosome and then introgressed these doubly marked segments into the genetic backgrounds of its sibling species, Drosophila simulans and Drosophila sechellia. Using these 21 lines (seven segments, three genetic backgrounds), we tested whether recombination rates within the doubly marked intervals differed depending on genetic background. We find significant heterogeneity among intervals and among species backgrounds. Our results suggest that a combination of both cis‐ and trans‐acting factors have evolved among the three D. simulans clade species and interact to affect recombination rate.     

Multivariate Analysis of Phenol in Freeze-Dried and Spray-Dried Insulin Formulations by NIR and FTIR

Dehydration is a commonly used method to stabilise protein formulations. Upon dehydration, there is a significant risk the composition of the formulation will change especially if the protein formulation contains volatile compounds. Phenol is often used as excipient in insulin formulations, stabilising the insulin hexamer by changing the secondary structure. We have previously shown that it is possible to maintain this structural change after drying. The aim of this study was to evaluate the residual phenol content in spray-dried and freeze-dried insulin formulations by Fourier transform infrared (FTIR) spectroscopy and near infrared (NIR) spectroscopy using multivariate data analysis. A principal component analysis (PCA) and partial least squares (PLS) projections were used to analyse spectral data. After drying, there was a difference between the two drying methods in the phenol/insulin ratio and the water content of the dried samples. The spray-dried samples contained more water and less phenol compared with the freeze-dried samples. For the FTIR spectra, the best model used one PLS component to describe the phenol/insulin ratio in the powders, and was based on the second derivative pre-treated spectra in the 850–650 cm⁻¹ region. The best PLS model based on the NIR spectra utilised three PLS components to describe the phenol/insulin ratio and was based on the standard normal variate transformed spectra in the 6,200–5,800 cm⁻¹ region. The root mean square error of cross validation was 0.69% and 0.60% (w/w) for the models based on the FTIR and NIR spectra, respectively. In general, both methods were suitable for phenol quantification in dried phenol/insulin samples.